REPORTS
8. R. Gao et al., Org. Lett. 3, 3719 (2001).
9. Details of 31P NMR spectra, phosphadioxirane decay
kinetics, and epoxidation studies are available as
supporting material on Science Online.
10. The upfield shift of the phosphorus signal indicates
an unusually large R-P-R angle for a pentacoordinate
phosphorus atom (R, aryl group), suggesting that the
geometry around 2 is best described as distorted
trigonal bipyramidal (19).
11. P. R. Bolduc, G. L. Goe, J. Org. Chem. 39, 3178 (1974).
12. M. S. Reynolds, A. Butler, Inorg. Chem. 35, 2378
(1996).
13. Coupling of the 17O nucleus (I ⫽ 5/2) to the 31P
nucleus (I ⫽ 1/2) was not observed, because of the
rapid quadrupolar relaxation, which leads to the very
large signal width. The axial and equatorial oxygen of
2 could not be differentiated by this method, probably because pseudorotation is so fast that they
become equivalent on the NMR time scale. Nahm et
al. have determined by MP2 single-point calculations
14.
15.
16.
17.
18.
that the activation energy for pseudorotation of the
dioxygen ligand in O2PH3 is only about 1 kcal/mol
(7).
M. Von Itzstein, I. D. Jenkins, J. Chem. Soc. Chem.
Commun. 164 (1983).
INTKIN is a noncommercial program developed by H.
Schwarz at Brookhaven National Laboratory.
K. C. Eapen, C. Tamborski, J. Fluorine Chem. 15, 239
(1980).
Time-resolved singlet oxygen luminescence quenching experiments are conducted by exciting a solution
containing the sensitizer (tetraphenyl porphyrin or
rose bengal) and varying amounts of substrate
(quencher) with a short (a few nanoseconds) laser
pulse and monitoring the 1O2 decay at right angles.
Competition experiments show that no physical
quenching occurred for phosphine 8, because the rate
of product formation was twice the rate of singlet
oxygen removal, as one would expect if all of the 1O2
was converted to product.
Protein Conformational Dynamics
Probed by Single-Molecule
Electron Transfer
Haw Yang,1* Guobin Luo,1 Pallop Karnchanaphanurach,1
Tai-Man Louie,2 Ivan Rech,3 Sergio Cova,3 Luying Xun,2
X. Sunney Xie1†
Electron transfer is used as a probe for angstrom-scale structural changes in
single protein molecules. In a flavin reductase, the fluorescence of flavin is
quenched by a nearby tyrosine residue by means of photo-induced electron
transfer. By probing the fluorescence lifetime of the single flavin on a photonby-photon basis, we were able to observe the variation of flavin-tyrosine
distance over time. We could then determine the potential of mean force
between the flavin and the tyrosine, and a correlation analysis revealed conformational fluctuation at multiple time scales spanning from hundreds of
microseconds to seconds. This phenomenon suggests the existence of multiple
interconverting conformers related to the fluctuating catalytic reactivity.
The conformational dynamics of biomolecules is crucial to their biological functions,
but these motions are usually spontaneous
and unsynchronized and thus difficult to
probe in ensemble-averaged experiments.
Recent advances in room-temperature singlemolecule fluorescence spectroscopy allow for
real-time observations of conformational motions and chemical reactions on biologically
relevant time scales (1–4). For example, by
observing the enzymatic reaction of a single
cholesterol oxidase molecule in real time, Lu
et al. deduced that the slowly interconverting
1
Department of Chemistry and Chemical Biology,
Harvard University, Cambridge, MA 02138, USA.
2
School of Molecular Biosciences, Washington State
University, Pullman, WA 99164, USA. 3Department of
Electronics and Information, Politecnico di Milano and
Centro Elettronica Quantistica e Strumentazione Elettronica Council of National Research, 20133 Milano,
Italy.
*Present address: Department of Chemistry, University of California, Berkeley, CA 94720, USA.
†To whom correspondence should be addressed. Email: [email protected]
262
conformers exhibit different catalytic reactivities (5). Recently, van Oijen et al. found
slow fluctuation in catalytic activity of single
DNA exonuclease molecules (6).
These studies recorded the changing reactivity of an enzyme molecule but did not directly
report the conformational motions of the enzyme. Measurements of fluorescence lifetimes
are more informative than measurements of fluorescence intensities, because the lifetimes are
sensitively dependent on protein conformations.
Electron transfer (ET) reactions are highly distance-dependent and have been observed
through the measurements of fluorescence lifetime for small single molecules (7). Here, we
show that the dynamics of excited state ET
reactions within an enzyme molecule can reveal
the presence of different conformations as well
as the time scale of their interconversion. Our ET
approach is sensitive to subtle distance changes
on the angstrom scale and is complementary to
the widely adopted fluorescence resonance energy transfer (FRET) technique, which has been
used for studies of single-molecule conformational dynamics on the nanometer scale (4, 8).
19. D. G. Gorenstein, in Phosphorus-31 NMR Principles
and Applications, D. G. Gorenstein, Ed. (Academic
Press, Orlando, FL, 1984), pp. 14 –15.
20. Y. Zhao, K. N. Houk, personal communication.
21. Support by the NIH–National Institute of General
Medical Sciences MBRS program (Award GM 08101)
is gratefully acknowledged. Acknowledgment is also
made to the Donors of The Petroleum Research Fund,
administered by the American Chemical Society, for
partial support of this research. J.C. was supported by
the NIH Biomedical Post-Baccalaureate Research Program (Award GM 64104).
Supporting Online Material
www.sciencemag.org/cgi/content/full/302/5643/259/
DC1
Materials and Methods
Figs. S1 to S3
14 July 2003; accepted 25 August 2003
To study protein dynamics without perturbation, we used a naturally fluorescent flavin
enzyme. The weak fluorescence from a single
flavin fluorophore in protein (the isoalloxazine of a flavin cofactor) required us to use
sensitive detection techniques. Another challenge was the extraction of dynamical information hidden in the single-molecule time
traces. Here, we show probing conformational dynamics with submillisecond time resolution and a broad range of time scales (9).
We studied a flavin-enzyme system, a
flavin reductase (Fre) from Escherichia coli
with a bound flavin, which is suggested to be
involved in DNA synthesis by means of the
activation of ribonucleotide reductase (10).
Fre catalyzes the reduction of a flavin by a
reduced form of nicotinamide adenine dinucleotide (NADH) through a hydride transfer
reaction. The crystal structure of the 26-kD
Fre has been solved both with and without
riboflavin (11) (Fig. 1A).
Flavin mononucleotide (FMN) and flavin
adenine dinucleotide (FAD) are two typical
flavin cofactors of Fre. The fluorescent
isoalloxazine of flavins (Fig. 1A, yellow)
serves as an ideal probe for conformational
dynamics (12). Free isoalloxazine such as
that of FMN (Fig. 1B, molecular structure) in
a pH 7 buffer exhibits a monoexponential
fluorescence decay with a 4.6-ns lifetime
when excited at 440 nm in an ensembleaveraged experiment (Fig. 1B, green curve).
In contrast, the decay of Fre-bound flavins is
much faster and is multiexponential. For example, the fluorescence lifetime decay of the
wild-type Fre/FMN complex (Fig. 1B, blue
curve) can be best fitted with four exponential decays: 0.008 ns [19 weight (wt) %],
0.050 ns (39 wt %), 0.25 ns (39 wt %), and
4.5 ns (3.6 wt %) (13). However, the ensemble-averaged measurements in Fig. 1 cannot
determine whether the multiexponential kinetics arise from static heterogeneity (in
which the molecules are statically different)
or dynamic fluctuations (in which a single
molecule changes with time).
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The fast fluorescence decay of isoalloxazine inside protein has been attributed to
the quenching of the excited state by ET
from nearby residues such as Trp or Tyr
( Y) (12, 14, 15). According to the crystal
structure, there are three tyrosines—Tyr35,
Tyr72, and Tyr116—near the isoalloxazine,
with edge-to-edge distances to the isoalloxazine of 4.5, 9.6, and 7.0 Å, respectively.
To identify the residues responsible for the
quenching of flavin fluorescence, we replaced the three tyrosines individually with
a serine (S) and generated three mutants—
Y35S, Y72S, and Y116S— by site-directed
mutagenesis. The fluorescence decays of
the two mutant complexes Y72S/FMN
(pink curve) and Y116S/FMN (orange
curve) are similar to that of the wild-type
Fre/FMN (Fig. 1B). A drastic increase of
fluorescence lifetime, however, was observed for the Y35S/FMN complex (red
curve). Therefore, we attribute the quenching of isoalloxazine fluorescence in wildtype Fre/FMN to ET from primarily the
35
closest Tyr (Fig. 1A, red) to the isoalloxazine. The reverse ET is expected to complete rapidly, returning isoalloxazine and
Tyr35 to their original states for repetitive
excitation (15).
The other flavin substrate, FAD (Fig. 1C,
molecular structure), binds Fre tightly in the
absence of NADH with a dissociation constant
Kd of ⬃29 nM, compared with the loose binding
of Fre/FMN, which has a Kd of ⬃1.5 ␮M (16).
We chose to do single-molecule measurements
on the wild-type Fre/FAD complex for its stability. By means of the molecular dynamics
(MD) simulations that were based on the Fre/
riboflavin structure, we obtained a representative configuration of the Fre/FAD complex (Fig.
1A) (16). The MD configurations indicate that
the isoalloxazine of FAD is enclosed in the
flavin-binding pocket with several hydrogen
bonds, whereas the adenine (Fig. 1A, gray) of
FAD extends to the exterior of the protein. On
average, the adenine tail forms two additional
hydrogen bonds with Fre, which explains the
higher affinity of FAD to Fre over FMN (16).
The isoalloxazine fluorescence of unbound
FAD is partially quenched by its flexible adenine
tail in aqueous solution (evident from the faster
decay of the green curve in Fig. 1C than that in
Fig. 1B). Based on the extended structure of
FAD in the protein, quenching by adenine is
negligible in the protein. Indeed, the multiexponential fluorescence decays of the wild-type or
mutant Fre/FAD (Fig. 1C) are similar to those of
Fre/FMN complexes. The fluorescence decay of
the wild-type Fre/FAD (Fig. 1C, blue curve) can
be best fitted with four exponential decays:
0.028 ns (25 wt %), 0.20 ns (52.1 wt %), 0.46 ns
(21.5 wt %), and 3.3 ns (1.2 wt %).
The fitting of the ensemble data by no
means reflects the true distribution of fluorescence lifetime. Assuming the population decay
is from a single electronic excited state in our
system, the (fluctuating) fluorescence lifetime
␥⫺1(t) can be expressed as: ␥⫺1(t) ⫽ [␥0 ⫹
⫺1
(t), where ␥0 is the fluoreskET(t)]⫺1 ⬇ kET
cence decay rate in the absence of the quencher(s), and kET is the ET rate. We seek to characterize the distribution and fluctuation of kET,
Fig. 1. (A) A representative structure of the Fre/FAD complex from an
MD simulation (16). The FAD substrate exhibits an extended conformation, with the fluorescent isoalloxazine ( yellow) in its binding pocket and
the adenine (gray) reaching the protein exterior. Also shown is Tyr35
(red), which dominates the quenching of flavin fluorescence in Fre. (B)
Ensemble-averaged fluorescence decays of free FMN (inset), wild-type
Fre/FMN, and mutant Fre/FMN complexes in a pH 7 buffer. The bumps
in the first nanosecond are due to convolution with the instrumental
response function. The results suggest that the fluorescence of the
wild-type Fre/flavin complex is predominantly quenched by Tyr35. (C)
Ensemble-averaged fluorescence decays of free FAD (inset), wild-type
Fre/FAD, and mutant Fre/FAD complexes in a pH 7 buffer.
www.sciencemag.org SCIENCE VOL 302 10 OCTOBER 2003
263
REPORTS
the information hidden in ensemble results but
extractable from a single-molecule experiment.
The Fre/FAD complex is tethered to the
quartz surface by a biotin-streptavidin linkage (13). Special care was taken to avoid
perturbations of the protein by the quartz
surface (17). Commercially available detectors do not provide the combination of high–
photon timing resolution, low– dark counting
rate, and high–quantum detection efficiency.
A single-photon timing module (SPTM) has
been designed and built based on the singlephoton avalanche diode (SPAD) devices developed by Cova et al. (18, 19).
Early single-molecule lifetime measurements
used the standard time-correlated photon counting method (7, 20, 21) to record histograms of
the delay times of fluorescence photons with
respect to the excitation pulses. Figure 2 is such
a histogram for a single wild-type Fre/FAD complex immobilized on the quartz surface. The
1
Single molecule decay
Occurrence (a.u.)
Fig. 2. Multiexponential fluorescence decay of a single wild-type
Fre/FAD complex [best fitted
with lifetime decay constants of
62 ps (77.3 wt %), 264 ps (14.3
wt %), and 2.26 ns (8.6 wt %)].
Also shown is the instrumental
response function (with 60-ps
full width at half maximum) and
a poor fit with a monoexponential decay. a.u., arbitrary units.
multiexponential single-molecule decay, similar
to the ensemble-averaged decay (Fig. 1C), indicates fluctuations of fluorescence lifetime at a
time scale longer than ␥⫺1. Similar multiexponential decays of single biomolecules have also
been reported (22, 23), in contrast to the monoexponential decays of isolated single-dye molecules (7, 20, 21). However, the time-scrambled
histograms provide no information about the
dynamics of lifetime fluctuation, which can be
obtained from single-molecule time traces.
Instead of acquiring only the histogram, for
each detected fluorescence photon with index p,
we recorded both the delay time with respect to
its excitation pulse, ␶p, and the chronological
arrival time, tp (9, 24) (Fig. 3A). Figure 3B
shows part of the time trace of ␶p for the same
complex in Fig. 2. If the ␥⫺1 does not fluctuate,
␶p is stochastic and has a single exponential
distribution with the mean of ␥⫺1. The fluctuating ␥⫺1 results in the multiexponential decay
0.8
Instrumental response
Single exponential fit
0.6
Multi exponential fit
0.4
0.2
0
Fig. 3. (A) Schematic
of a train of laser excitation pulses (bell
shaped) and detected
fluorescence photons
(bars). For each detected photon, the delay time with respect
to the excitation pulse
␶p and the chronological arrival t p are recorded. (B) Part of the
time trace of the fluorescence photon delay
time of the same wildtype Fre/FAD complex
as in Fig. 2. (C) Part of
the time trace of the
fluorescence lifetime
of the same wild-type
Fre/FAD complex as in
(B) obtained by the
MLE fitting of every
100 detected photons.
264
0
1
2
3
4
5
τp (ns)
6
7
8
9
10
of the ␶p histogram in Fig. 2 for all the photons
in the entire time trace.
To evaluate how ␥⫺1changes with time,
the conventional method is to bin many
photons for an average ␥⫺1. For example,
Fig. 3C shows part of the time trace of ␥⫺1
by binning every 100 photons, in which
large fluctuation of ␥⫺1 is indeed evident.
With the mean fluorescence count rate of
500 counts/s in our experiment, the time
window corresponds to a mean of 200 ms.
We used the maximum likelihood estimation (MLE) to determine ␥⫺1 (13, 25). It
has been shown that 100 detected photons
are sufficient to determine the single exponential decay constant by MLE. However,
the binning limits the time resolution of
dynamical changes; therefore, fluctuations
within the time bin are averaged out.
The dynamics of fluctuation can be characterized by the correlation functions of ␥⫺1
fluctuation, in particular, the autocorrelation
function, C(t) ⫽ 具␦␥⫺1(t)␦␥⫺1(0)典, where
␦␥⫺1(t) ⫽ ␥⫺1(t) – 具␥⫺1典 and the brackets
denote averaging over time. If there is no
fluctuation of ␥⫺1, then C(t) ⫽ 0. When there
are two interconverting states with different
lifetimes, C(t) is a single exponential decay
with a decay constant equal to the sum of the
forward and backward conversion rate constants (9). Multiple conformational states normally result in multiexponential decay C(t),
characterizing the time scales of ␥⫺1 fluctuations, with C(0) being the variance of ␥⫺1. C(t)
can be calculated from the time trace of ␥⫺1 in
Fig. 3C, although with a poor time resolution.
Accurate knowledge of ␥⫺1(t) from long
time binning is not required to determine
C(t), which itself is a statistically averaged
property. The time resolution of C(t) can be
significantly improved if C(t) is calculated on
a photon-by-photon basis (9, 13). We obtained a time resolution of C(t) comparable to
the reciprocal of the average count rate. The
time resolution in principle can approach that
of the ever-increasing length of MD simulation trajectories (26), which portends direct
comparison between single-molecule experiments with MD simulations in the future.
Consequently, our approach permits measurements of C(t) on a broad range of time
scales for the given time-trace lengths, limited by photobleaching. In our analysis, background photons will not contribute to C(t ⬎
0), because they are not correlated with fluorescence photons from the single molecule.
Figure 4 shows the C(t) of a wild-type
Fre/FAD complex, with fluctuation occurring at
a broad range of time scales, from hundreds of
microseconds to tens of seconds. This information was not available from previous ensembleaveraged experiments. The green dashed line in
Fig. 4 is a fit with a stretched exponential,
exp[–(t/␶0)b], where b ⫽ 0.30 and ␶0 ⫽ 54 ms.
The stretched exponential is simply a phenom-
10 OCTOBER 2003 VOL 302 SCIENCE www.sciencemag.org
REPORTS
enological fit that conveniently describes dynamics spanning decades of time scales with
only two adjustable parameters rather than multiple exponentials. Fluorophores that exhibited
single exponential fluorescence decay showed
zero C(t ⬎ 0) (fig. S5). For every wild-type
Fre/FAD complex that emits a sufficient number of photons (⬎100,000) to give visible correlation before photobleaching, we observed
similar stretched exponential C(t) with b varying from 0.17 to 0.31. We did not observe
noticeable power dependence of C(t) in the
excitation power range from 0.5 to 3 ␮W at the
sample (13). Had the fluctuations been photoinduced, C(t) would have decayed faster at
higher excitation powers, suggesting that the
lifetime fluctuations are in fact spontaneous.
We next discuss the origin of kET(t) fluctuations. On the basis of Fermi’s golden rule,
the nonadiabatic ET rate is kET ⫽ (4␲2/
h)V 2F, where h is Planck’s constant, V is the
electronic coupling between the two diabatic
states (DA and D⫹A–), and F is the FranckCondon weighted density of states (27, 28).
We then considered whether the kET variation
arises from the fluctuation of V or F.
At room temperatures, F takes a simple Arrhenius form (27, 28), kET ⫽ (4␲2/
h)V 2(4␲kBT ␭)⫺1/2exp[–(⌬G ⫹ ␭)2/4␭kBT],
where kB is the Boltzmann constant, T is temperature in kelvin, ⌬G is the free energy difference between DA and D⫹A–, and ␭ is the reorganization energy. Thermal fluctuation of ⌬G
could lead to fluctuation of kET as in photosynthetic reaction centers (29, 30). For the electronically excited FAD/tyrosine system, the kET is
close to the maximum rate at which –⌬G ⬃ ␭ ⫽
28 ⬃ 40kBT (0.7 to 1.0 eV) (14). Under this
activationless condition, kET is relatively insensitive to thermal fluctuations in ⌬G. If ⌬G variation (denoted as ⌬⌬G) is the sole source of kET
fluctuation, the large amplitude of the observed
kET fluctuation (a difference of more than one
order of magnitude, with time constants ranging
from 30 ps to 3 ns) would result from an unphysically high ⌬⌬G ⬇ 16 ⬃ 20kBT.
However, the electronic coupling V exhibits an exponential dependence on the edgeto-edge distance R between D and A such that
0
exp[–␤R(t)], where ␤ has been
kET(t) ⫽ k ET
experimentally determined to be 1.0 to 1.4
Å⫺1 for proteins (31, 32). Distribution of ET
rate originating from a (frozen) distribution
of donor-acceptor distances was previously
observed for photosynthetic reaction centers
(33). V is also dependent on the relative
orientations of D and A (34). Typically, however, the torsional angles of Tyr residues in
the protein interior are confined to a narrow
range (35). Because of the exponential distance dependence, R fluctuation has a much
stronger effect on the ET rate than the effects
of the driving force and orientation. We thus
attribute the large lifetime fluctuations (30 ps
to ⬃3 ns) primarily to R fluctuation.
We next determined the distribution of the
isoalloxazine-Tyr35 distance, R. First, we obtained a distribution of ␥⫺1 from the 100-photon binned time trace of ␥⫺1 (Fig. 3C). The
distribution is coarse-grained because the fast
fluctuation within the time bin is averaged out.
The corresponding coarse-grained lifetime
probability density P(␥⫺1) can be calculated
(Fig. 5A). P(␥⫺1) is converted to the probability density P(R) assuming ␤ ⫽ 1.4 Å⫺1 (Fig.
5B). Finally, the potential of mean force for the
isoalloxazine-Tyr35 pair is obtained by taking
the logarithm of P(R): V(R) ⫽ –kBT ln[P(R)].
V(R) can be approximated by a harmonic potential within the thermally attainable region
(Fig. 5C) (13). The best fit of P(␥⫺1) (13) with
V0(R) ⫽ kBT(R – R0)2/2␪ (Fig. 5C, dashed line)
gives the variance of R, ␪ ⫽ 0.19 Å2. ␪ compares favorably with the crystal-structure data,
which gives average atomic-mean-square dis-
2
placements of 0.10 and 0.25 Å for the isoalloxazine and Tyr35, respectively. This agreement
further corroborates our assignment of kET fluctuation to primarily R fluctuation.
The potential of mean force V(R) is a timeaveraged function that does not contain dynamical information. To gain an understanding of the
observed dynamics, we first modeled R fluctuation as a fictitious particle undergoing Brownian
diffusion on the potential V0(R) and obtained the autocorrelation function CB(t) ⫽
0 ⫺2
) exp(2␤R0 ⫹ ␤2␪)[–1 ⫹ exp(␤2␪e–␩t)]
(k ET
where ␩ is a drift coefficient (9). However, CB(t)
(Fig. 4, pink dashed line) does not fit the measured C(t) (Fig. 4). The Brownian diffusion
model is inadequate because it implies one characteristic trapping time (associated with ␩) at a
particular R, which does not hold for complex
systems like proteins (36, 37). The trapping
time, ␶, at a particular R, might assume a power-
www.sciencemag.org SCIENCE VOL 302 10 OCTOBER 2003
Fig. 4. Autocorrelation function
of fluorescence lifetime fluctuation of the same wild-type Fre/
FAD complex as in Figs. 2 and 3,
plotted in linear logarithmic
scale in time. Also shown are
good fits with a stretched exponential and the anomalous diffusion model and a poor fit with
the Brownian diffusion model.
The C(t) unravels protein conformational fluctuation spanning a
broad range of time scales.
Fig. 5. (A) Distribution
of fluorescence lifetimes obtained from
the time trace in Fig.
2D. (B) Distribution of
the FAD-Tyr35 edgeto-edge distance derived from (A). (C) Potential of mean force
calculated from (B).
The dashed lines in
(A), (B), and (C) are
distributions according to the fit to a harmonic potential of
mean force around R0
and with variance ␪ ⫽
0.19 Å2. (Inset) A
sketch of a rugged
“transient” potential
resulting from the
short-time projection
of 3D motions of the
protein to the experimentally accessible R
coordinate.
265
REPORTS
law distribution, 1/␶␣ ⫹ 1 (0 ⬍ ␣ ⬍ 1), which has
no finite mean (38). This situation is referred to
as the subdiffusion regime of anomalous diffusion. Subdiffusion in a potential can be described by the fractional Fokker-Planck equation recently developed by Klafter and co-workers (38). Using V0(R) as the potential, we
obtained the correlation function (9)
5.
6.
7.
8.
9.
10.
11.
12.
0 ⫺2
C A(t)⫽(k ET
) exp(2␤R 0⫹␤2␪)
(exp{␤2␪ exp[–␩␣t ␣/⌫(1⫹␣)]}–1)
where ␩␣ is the generalized drift coefficient
and ⌫(z) ⫽ 兰0⬁y z–1e–ydy. CA(t) (Fig. 4, red
solid line) fits well with the measured C(t),
with ␣ ⫽ 0.31 and ␩␣ ⫽ 2.19 s–␣.
The physical picture behind CA(t) can be
understood as follows: The multidimensional energy landscape of the entire protein has many
local minima, each corresponding to a conformational state. The conformational states have
vastly different trapping times because the free
energy barrier heights for the interconversion
among them are broadly distributed. Projection
of the time-varying 3D structure of the protein
to the experimentally accessible R coordinate
results in a broad ( power-law) distribution of
trapping time at a particular R. Such a projection of 3D motion to the R dimension within a
short period of time gives rise to a rugged
“transient” potential (Fig. 5C, inset). With its
long time average being the smoothed V(R), the
rugged potential with fluctuating free energy
barriers results in the subdiffusion and the
stretched exponential C(t).
The picture of rugged energy landscape has
been advocated by Frauenfelder based on photodissociation experiments with liganded
hemeproteins (39). Reminiscent of glassy systems (40), ligand recombination kinetics at low
temperatures exhibited dispersed kinetics because of a frozen distribution of conformations,
the interconversion among which occurs at elevated temperatures. Even at room temperature,
stretched exponential relaxation of protein conformations has been observed (41). The ensemble-averaged experiments, however, could hardly distinguish dynamical fluctuation and static
heterogeneity, nor could they extract the interconversion dynamics. It is important to stress
that our single-molecule experiments directly
measure the equilibrium fluctuation rather than
nonequilibrium relaxation as in the previous
experiments, and they provide a quantitative
measure of the protein conformational memory
at room temperature. A dynamic entity, an enzyme exhibits different catalytic activity (5, 6)
because of its fluctuating conformations.
References and Notes
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3. W. E. Moerner, M. Orrit, Science 283, 1670 (1999).
4. S. Weiss, Science 283, 1676 (1999).
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Supporting Online Material
www.sciencemag.org/cgi/content/full/302/5643/262/
DC1
Materials and Methods
Figs. S1 to S6
References
16 May 2003; accepted 25 August 2003
Periodic Mesoporous
Organosilicas Containing
Interconnected [Si(CH2 )]3 Rings
Kai Landskron,1 Benjamin D. Hatton,1,2 Doug D. Perovic,2
Geoffrey A. Ozin*1
A periodic mesoporous organosilica composed of interconnected three-ring
[Si(CH2 )]3 units built of three SiO2(CH2 )2 tetrahedral subunits is reported. It
represents the archetype of a previously unknown class of nanocomposite materials in which two bridging organic groups are bound to each silicon atom. It can
be obtained with powder and oriented film morphologies. The nanocomposite is
self-assembled from the cyclic three-ring silsesquioxane [(EtO)2Si(CH2 )]3 precursor
and a surfactant mesophase to give a well-ordered mesoporous framework. Low
dielectric constants and good mechanical stability of the films were measured,
making this material interesting for microelectronic applications. Methylene group
reactivity of the three-ring precursor provides entry to a family of nanocomposites,
exemplified by the synthesis and self-assembly of [(EtO)2Si(CHR)][(EtO)2Si(CH2 )]2
(where R indicates iodine, bromine, or an ethyl group).
Materials with well-defined pores belong to
the most interesting classes of compounds,
because they can be developed into organicinorganic nanocomposites with unique catalytic, sensor, optical, magnetic, or electrical
properties, whereby the organic functional-
ization of an inorganic porous host can play
an important role (1). An exciting approach to
organic-inorganic nanocomposites takes lessons from the synthesis of periodic mesoporous silica MCM41, where an organic mesophase is replicated in silica with the use of
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